Taxila Lab

Discovery


Our discovery process works on the metaphor of 'conversation' where our server better understands the consumer's needs. This makes it equally usable across all the channels including voice. The discovery experience is also personalized for individual consumer and the channel of access.

Recommendation
We provide a sophisticated recommendation platform that can make more precise recommendations and dramatically increase consumption. The recommendation engine is tightly coupled with the discovery engine so that both can benefit from each other. In particular, our recommendation engine is able to use the "reason for consumption" which makes it better than the other recommendation engines.

We work very closely with our customers (such as operators, online media and entertainment brands, eCommerce providers) to customize and tune the recommendation engines for the specific domains, as one recommendation engine cannot serve all domains, and the recommendation engine needs to evolve with time.

Metadata Management
Top quality metadata is the key to realizing Long Tail on digital channels. We have built the world's most advanced (and perhaps the only) metadata management system that reduces the cost of metadata creation significantly (approx by 70%) and dramatically improves the quality. The metadata in our metadata engine can be published to our discovery and recommendation engine with a single click of a button.

Analytics
We closely track all the consumer interactions on our discovery and recommendation engines. The data so collected can be analyzed through our analytics dashboard which provides detailed reports and allows multi-dimensional analysis (slicing and dicing). This enables the online service provider to get a detailed 360 degrees view of its business and customers.

Ad Server
Our ad server allows ad injection on all the channels we support (mobile, voice, Internet,...). The interactive nature of our discovery and recommendation engines provides us with deep understanding of the consumers. Our ad server uses this understanding to serve more targeted ads (more than the keyword based networks such as Google Ad Sense) by leveraging the profile (past behavior) and context (current activity) of the consumer.


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